8 results about "Patient input" patented technology

The following relates generally to improved clinical symptom analysis. In some embodiments, one or more processors: (1) receive patient input data; (2) obtain patient survey data representing the patient's condition; (3) determine a trend in the patient survey data using a determination algorithm; (4) apply the generative AI algorithm to the patient input data, the patient survey data, and the trend in the patient survey data to produce a report of the trend of the patient's condition; and / or (5) display the report on a display device.

The following relates generally to improved clinical symptom analysis. In some embodiments, one or more processors: (1) receive patient input data; (2) obtain patient survey data representing the patient's condition: (3) determine a trend in the patient survey data using a determination algorithm; (4) apply the generative Al algorithm to the patient input data, the patient survey data, and the trend in the patient survey data to produce a report of the trend of the patient's condition; and / or (5) display the report on a display device.

A decision support system that aids healthcare practitioners in making more informed clinical decisions and avoiding errors related to diagnosis and treatment of diseases. The system utilizes several data points from the patient history and clinical findings input by the patient and the doctor, to help the doctor make a more accurate diagnosis and develop a more informed treatment plan that incorporates not just drugs and procedures, but also dietary and lifestyle interventions. A system of the present disclosure comprises dosage calculator, symptom checker, differential diagnosis, drug interaction checker, side effect checker, nutritional analyzer and drug-food interaction checker input pathways and corresponding database compartments. Output data is generated in correspondence with patient input data and stored on a database server, where it is correlated with patient outcomes over time and improved through machine learning.

A computer-program product, system, and method of retrieving electronic health records (EHRs) of a patient including: requesting legally compliant permission from a patient to access a plurality of EHRs of the patient from a plurality of separate electronic storage devices storing at least one of the EHRs of the patient in a non-transitory computer-readable recording medium; receiving an access request from the patient via a natural language interface to retrieve the EHRs of the patient from the separate electronic storage devices; processing the access request using a generative artificial intelligence (AI) model having a unique licensing number assigned thereto; generating via the AI model a structured access request query; and sending via a communication network the structured access request query with the legally compliant permission to the separate electronic storage devices and thereby retrieving the EHRs.

An electronic device for de-identifying personal information in clinical information text according to an embodiment comprises: a memory; and a processor for training a machine learning-based de-identification tag generation model on the basis of annotation data indicating a de-identification category for each token of training text and a training dataset including the training text, providing clinical information text for a patient input by medical personnel to the trained de-identification tag generation model, so as to output a de-identification category for each token of the clinical information text, and changing a token corresponding to personal information in the clinical information text into an expression indicating non-personal information on the basis of the output de-identification category.

A wearable medical system (WMS) includes a dongle having a cable, cancel switch, microphone, and processor. The processor determines, based on patient input, whether a shock criterion is met and, if met, causes an output device to provide a human-perceptible indication (HPI). After a preset delay following the HPI, the processor discharges stored electrical charge through a therapy electrode to deliver a shock to a patient if the cancel switch has not been actuated. If the cancel switch is actuated within the preset delay, discharge of the stored electrical charge is prevented.

This disclosure relates to systems and methods for managing patients of knee surgeries. A pre-operative patient questionnaire user interface is associated with a future knee operation of the patient. Patient input data is indicative of answers of a patient in relation to the pre-operative patient questionnaire. A processor of a computer system evaluates a statistical model to determine a predicted satisfaction value indicative of satisfaction of the patient with the future knee operation. The statistical model comprises nodes stored on data memory representing the patient input data and the predicted satisfaction value, and edges stored on data memory between the nodes representing conditional dependencies between the patient input data and the predicted satisfaction value. The processor then generates an electronic document comprising a surgeon report associated with the future knee operation to indicate to the surgeon the predicted satisfaction value.

This disclosure relates to generating large language model (LLM)-based neurostimulation programming recommendations. An example method for large language model (LLM)-based neurostimulation programming recommendations comprises receiving patient inputs from a patient undergoing neurostimulation from a programmed neurostimulation device, programmer input data related to the programmed neurostimulation device, or both; querying a trained LLM with the patient inputs, the programmer input data, or both, to generate a programming recommendation, a recommended action, or both; providing a representation of the programming recommendation, the recommended action, or both; receiving an input to initiate the programming recommendation, the recommended action, or both; and initiating an action for the neurostimulation treatment, based on the input to initiate the programming recommendation, the recommended action, or both.